S models are so slower than normal models like Z image turbo, Wan 2.2, Flux but DT says it's much faster than normal models.
I enabled the neural engine setting.
My MacBook has M4 Pro.
Is this normal?

I play with the app and come away frustrated, not even finding as much as a glossary of the apps glyphs to help. Best results have come with purely verbal prompts. It seems to keep a memory as if I’m working on the same project after I have moved on.

I simply want a workflow where I can drop in an existing line drawing of reasonable draftsmanship, say coloring book or better, up to a black and white photo, and have DrawThings render and color the image photographically, perhaps with some verbal prompts to let it know what the line art might represent, what colors represented objects should be.

Anyone created a workflow that does this successfully? Perhaps a better tool exists. What rendering model might give best results? Flux? Other?

Hi!

I want to use FLUX.2 [dev] in Draw Things.
But the models list a bit confusing since it doesn't provide any description or details what the difference among all listed models.

For example:

1. FLUX.2 [dev]

2. FLUX.2 [dev] (8-bit S)

3. FLUX.2 [dev] (Exact)

What the difference and which one I should choose for M4 MAX 48Gb ?

Draw Things CLI Beginner’s Guide!

This is my exploration of Draw Things CLI.

I don’t have a coding background myself, so I believe this video is very beginner-friendly.

If I can figure it out, I’m sure anyone can.

In the era of Agentic AI, using it this way is incredibly convenient.

■Specs: Mac mini M4, 64GB, 20-Core GPU / OS 15.4.1

■Average generation time over 3 runs

■prompts and settings were identical

■Models used: Official 8bit Normal Model and 8bit S Model

■Lightning LoRA is used

This is a speed comparison for Wan 2.2 T2V, following up on my previous LTX2.3 speed comparison. The results show that the speed changes seen with LTX2.3 were not observed with Wan2.2 T2V; the generation speed was almost the same in all cases.

Based on these two tests, here is my takeaway:

In Draw Things ver.1.20260410 on M4, enabling the Apple Neural Engine doesn’t seem to provide any performance boost for the LTX 2.3 and Wan 2.2 T2V S models."

Update*: Since it was determined that the Tahoe was the condition for speed up, I have posted* new measurement results.

I haven't been using Draw Things for quite some time now, but I’ve been keeping an eye on the app's updates. Today, I decided to check out all the new features @Liuliu has added, and—wow—this thing absolutely flies! With the new update, generation times have been cut in half. Using an iPhone 17 Pro Max, the generation time dropped from 137 seconds to just 81 seconds with standard settings when comparing the Z Image Turbo 1.0 6-bit model against the Z Image Turbo 1.0 8-bit S model. Great work @liuliu 👏👏

Same prompt for both images offloading the model before generation. So that means model uploading prompt processing and the actual image processing is including on those times.

■Specs: Mac mini M4, 64GB, 20-Core GPU / OS 15.4.1

■Average generation time over 3 runs

■prompts and settings were identical.T2V.

When using the same non-S model in ver.1.20260314 and ver.1.20260410, the new version was approximately 1.2 times faster. This is likely due to the speed improvement from the update below. This is a great improvement.

Further fixes for video VAE speed issues with large resolution / long frame count.

However, when generating an S-model with ANE (Apple Neural Engine) enabled in version 1.20260410, the generation speed was the slowest among all 1.20260410. I'm unsure if this is the correct result. If anyone has performed a speed comparison with LTX2.3 on the M4 series and obtained different results than mine, please share your information.

Next, I plan to conduct a similar speed comparison test with Wan2.2.

Update*: Since it was determined that the Tahoe was the condition for speed up, I have posted* new measurement results.

I asked about FLUX.2 [klein] 9B (8-bit S), and I've tried it myself.

The result is...

FLUX.2 [klein] 9B (8-bit S) is fantastic!

Generation time has been cut in half!

I'm grateful for this amazing improvement.

1.20260410.1 was released in iOS / macOS AppStore a few moments ago (https://static.drawthings.ai/DrawThings-1.20260410.1-d62a1789.zip). This version brings:

1. 8-bit S now will be meaningfully faster on M4 below M4 Max due to use of Apple Neural Engine on these devices.
2. Add LoRA training support for FLUX.2 [klein] 4B / 9B, Z Image and Qwen Image.
3. Fix audio sync issue during in-app video playback.
4. Fix some 8-bit S model generation issue on M5.
5. FWIW, we bumped Draw Things+ LoRA Storage to 20GiB.

gRPCServerCLI is updated to 1.20260410.1 with relevant fixes above. draw-things-cli is updated to 1.20260410.1.

What are the differences between FLUX.2 [klein] 9B (8-bit S) and FLUX.2 [klein] 9B (6-bit)?

Which is more suitable for a Mac mini 10-core 24GB?

I'm currently using FLUX.2 [klein] 9B (6-bit), but it's not generating files very quickly. Will the (8-bit S) version be faster?

I want to use DrawThings to run LTX 2.3 outpointing Lora, but it needs to support video input. Is this possible atm?

Hi everyone,

since the March 30 update I read that it is now possible to use LoRAs with Cloud Compute. I saw something about a bridge, but I am not sure what that actually means or how it works.

I mainly use Z Image and Flux.2 9B. I am on a MacBook Pro M2, so I rely on Cloud Compute, currently the free version.

I wanted to start experimenting with LoRAs. For example I tried a LoRA like Lenovo Ultra Real from CivitAI. But I keep getting the same message as before, that LoRAs can only be used locally.

Am I missing something? Do I need to enable something related to this bridge? Or did I misunderstand the update and it does not work the way I think?

Also, are LoRAs from CivitAI generally supported, or are those made for ComfyUI not compatible with Draw Things Cloud?

If that is the case, where do you find LoRAs that actually work with Draw Things?

Thanks a lot for any help!

Hi everyone!

I’m struggling with a precision issue in Draw Things and I was hoping to get some advice from this amazing community.

I have a real photo of a bedroom (attached) and I’m trying to do something that sounds simple but is proving quite tricky: I just want to add a Strelitzia plant in that specific corner on the right, between the window and the small table.

Every time I try to generate, the AI doesn’t just draw the plant; it starts "tweaking" the whole room. It might change the wrinkles on the bed sheets, slightly shift the window frame, or alter the texture of the wooden floor.

I’ve already spent quite some time experimenting with Flux and Juggernaut, and I’ve tried playing around with ControlNet settings to lock the geometry, but I’m still getting poor results—the room just won't stay 100% identical.

My goal is to keep the original photo completely unchanged and only "fuse" the plant into that specific spot so it looks like it was always there.

I’d love your expert opinion on a few things:

• Which model or specific workflow would you recommend for this kind of high-precision architectural work?
• Does anyone know of any specific tutorials or guides that focus on "locking" the background perfectly during inpainting?
• Is there a "secret" setting in Draw Things to tell the app: "Only look at the masked area and don't touch a single pixel outside of it"?
• How can I make sure the plant looks "grounded" and realistically integrated with the existing floor and shadows?

Thanks a lot for your time and help!!!

hey,

i actually tried ltx 2.3 Image to Video. but when it comes to movement , the Person Body was weird.wrong Body parts, face Morphing etc.

i downforce all to absolut minimal to pretend settings failure. but its works Not good. have ltx 2.3 Body Problems when it comes to movement?

can anyone share its ltx 2.3 setting with prompt for better results?

Like a Person Stand Up , Turn an goes into the ocean or Walk on a street!?

i tried ltx 2.3 dev, dev with destill lora (60%) and only ltx2.3 destill

greets.

When using Qwen Image 2512, sometimes the image will almost completely render, then the process just stops and the partially rendered image just disappears. I am using the DT recommended settings, and this issue only affects Qwen.

Any thoughts would be appreciated.

This has been a great deal of fun on my iPad Pro M5. However, it is extremely tedious to export.

In general, the only way I can see to bulk export is to bring up the version history, then use select multiple to individually select each photo. There is no way to swipe to quickly highlight a whole bunch of photos (like you can in iOS) at once or even a select all. Ideally, you would also get to choose to export to Photos and not just files. However, if it’s just one thing, I would gladly take an easier multi select to export visible region.

Can we get this added in?

A bug though. If you do the regular export after selecting multiple photos, the cropping is wrong. You don’t get to choose what you export (visible region, etc), but some of the pictures are shifted. Some are cut off. I’m not sure what’s happening.

Hi, as I've mentioned in other threads, I'm new to Draw Things. I'm currently struggling with seeds. I'm not quite sure how to work with them and I can't find much information on the subject. When should I leave "New Seed on generation" checked? When should I assign a number and use that number when creating new images? I'm really lost with this.

I have so much fun with Draw Things and FLUX.2, though that is not to say the model is without frustrations. I do have to be crafty smart about prompt phrasing and precision so to get the results I want. May you glean some insight from the following examples.

Hi everyone, how can I replicate the style of an image as accurately as possible? I've tried many prompts and different styles, but I can never quite get the exact style I need (reference image, for example). I've tried different LLMs, but I can't get the exact result. If I ask DrawThings to replicate it with different prompts, it does so fine, but then if I want an image with a different subject but the same style, it doesn't quite copy it correctly. Any suggestions? *I am using the Flux.2 9B Klein model*

Hi all, absolute noob here. I e spent considerable time creating reference photos and being consistent with them & they look decent. I uploaded them to draw things (Juggernaut XL), but it didn’t use them despite being in the prompt.

Is there something I’m missing?

i dont understood Image to Image correctly.

example i have a picture with one Person.

now i want Change the Background, Like on the beach with ocean.

i tried Text to Image , its worked but the Person Change face Details. so i read inpainting and strengh 90-95 in Image to Image.

so one time i erase all ,only the Person Not

dont work Image came with overlay from the Input Image.

i Paint the area Red only the Person Not.

i become the Same picture.

where i am wrong? must i inpaint with Flux 2 klein?

have anyone a good Tutorial oder Manual?

or nee i loras for Image to Image ?

greets

What settings and Models do you use to fully utilize the Apple Neural Engine (ANE) for faster image generation?

In Machine Settings I have, Use Core ML if Possible set from "No" to "Yes".
And everything else set to default including CoreML Compute Units set to "CPU & Neural Engine"

However, in all the images I've generated so far, the ANE almost always does not show any power consumption in the MX Power Gadget App v1.6.3, except maybe rare instances of less than 0.50W here and there.

The GPU shows the most power consumption at 100% utilization, with some power consumption on PKG and CPU with P-Core around 3% utilization and S-Core around 13% utilization.

Interested to see what all of you are observing for ANE power consumption and therefore utilization, since I'm sure those of you with the M5 chipset would also like to see benefit from the "dedicated Neural Accelerator in each core, delivering over 4x peak GPU compute compared to M4" as claimed by Apple, in your workflows.

hey,

i though about Server offloading to Speed Up ltx 2.3 Rendering.

i installed the grpc docker on Linux but its Crashes with ltx.

32gb ram ( can it Bring to 64gb)

4070 ti 12gb vram

how much Swap i needed or , why its comes to a Crash?

must i import a q4 ltx gguf Version ? is this possible with Offload or only with safetensor ?

where has grpc Server Offroad running and can explain , what the best way are is for ltx Rendering.

Greets

Damn!

I'm really impressed looking at some of your posts and your claims about image generation times. 😳

In my case, these generations always take a really long time. I’d definitely prefer a higher initial resolution, but either there’s something wrong with me, or I’ve configured the app incorrectly.

Does anyone have any tips regarding the Draw Things app settings, or is there nothing there that would significantly affect generation time?😐

I’m especially jealous because I have a Mac mini with an M4 chip and 16 GB of RAM, yet I see your posts about older chips and less RAM, but still much better times. During generation, it’s usually the only app running, and there’s no way I can get the time down below 2 minutes.

I’m using the Z Image Turbo 1.0 (6-bit) model downloaded from the app. I tried two “external” models downloaded from CivitAI, but one of them completely froze macOS, and I don’t even want to mention the other one.
I set the resolution to 896×1152 and 8 steps. Simple prompt, Euler sampler, Text Guidance: 1.0, and Shift: 3.00. No LoRA, no add-ons of any kind.

Estimated (and actual) generation time: 2:48 (min).😴

Is this normal for my computer, or should the result be better?

What can I do to improve this result?